菌群群体感应控制机制及优化算法研究

项目名称： 菌群群体感应控制机制及优化算法研究

项目编号： No.61502318

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 其他

项目作者： 申海

作者单位： 沈阳师范大学

项目金额： 21万元

中文摘要： 细菌属于最简单的单细胞生物，存在于地球上至少具有 35 亿年历史，见证并参与了漫长的生物进化过程。细菌的群体感应行为是保障细菌在时变环境中适应性生存的必要条件，同时，群体感应机制也是一个复杂动力系统，呈现出多样性、复杂性和动态性。因此，研究群体感应机制对复杂动态系统的建模与优化具有重要的借鉴作用。本项目将基于菌群生存环境结构模型与群体感应控制机制的研究，设计群感机制对个体和群体的典型控制行为，包括个体觅食行为、种群规模自适应调整行为和多重信号自适应响应行为的控制方法；在此基础上，从复杂自适应系统角度建立菌群群体感应调控模型，通过虚拟仿真环境和对提出的群体感应调控模型进行分析与验证；最终提出基于细菌群体感应的新型优化计算方法，为复杂工程领域的问题求解提供新的模型与方法。本项目的研究把复杂系统的研究推向与微生态系统相结合的智能领域，为工程科学与生物科学的交叉与融合提供了新的研究视角。

中文关键词： 群体智能；优化算法；群体感应；动力学模型

英文摘要： Bacteria belongs to the simplest single cell organisms, exist on the earth at least 3.5 billion years, witness and participate the long biological evolution process. The bacterial quorum sensing behavior is a necessary factor for their survival adaptation in time-varying environment, Meanwhile, the quorum sensing mechanism is also a complex dynamical system, showing diversity, complexity and dynamic feature. Therefore, the study of quorum sensing mechanism offers an important reference function to the complex dynamic system modelling and optimization. This project will be based on survival environment structure model and the quorum sensing control mechanism research, design individual and population adaptive control method of the typical behavior under the quorum sensing system, typical behavior include individual forage behavior, population size adaptive adjust behavior and multi sensing signals response behavior; On this basis, from the perspective of complex adaptive system, establish quorum sensing control mode, through the virtual simulation environment and the analysis of the system characteristics of quorum sensing control model, reveal the mode and the law between the bacterial quorum sensing mechanism and the population evolution; Finally proposed bacterial quorum sensing optimization method, offers a new model and the method for complex engineering problem. This research project would push the research of complex systems with the research of micro-ecological system to intelligence field, and provides a new research perspective for crossover and integration of engineering science and biological sciences.

英文关键词： Swarm Intelligence;Optimization Algorithm;Quorum Sensing;Dynamics Model